👀 Views: 0 💬 Answers: 1 📅 Created: 2025-06-12

r dataframes lapply R

I'm collaborating on a project where After trying multiple solutions online, I still can't figure this out. I'm trying to apply a function using `lapply` on a list of data frames, but I'm working with an behavior due to differing column names in the data frames. My data frames are stored in a list called `df_list`, and I want to calculate the mean of a column named `value`, which exists in some data frames but not in others. Here’s the code I’m using: ```r result <- lapply(df_list, function(x) mean(x$value, na.rm = TRUE)) ``` However, I get the following behavior when running it: ``` behavior in mean(x$value, na.rm = TRUE) : x$`value` is NULL ``` I understand that not all data frames in `df_list` have the `value` column, but I’m not sure how to handle this situation gracefully. I've tried using `if ("value" %in% colnames(x))`, but that leads to a more complex structure that isn’t straightforward for the `lapply` function. I would prefer a solution that allows me to skip over those data frames without the `value` column and return a list with `NA` for those entries instead. Is there a cleaner way to achieve this? I'm using R version 4.2.2 and `lapply` seems the most appropriate function for this task, but I’m open to suggestions if there’s a better approach. For context: I'm using R on Windows. Has anyone else encountered this? My team is using R for this CLI tool. Any pointers in the right direction?